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The "Cheating vs. Not Cheating" image classification application is designed to automatically distinguish between images that depict cheating behaviors and those that do not. Leveraging advanced machine learning algorithms, the system analyzes visual features in images, training on a dataset labeled with instances of cheating and non-cheating activities. This application aims to provide accurate and fast classification results, useful in scenarios like monitoring exams, detecting dishonesty in sports, or identifying unethical behavior in various contexts. The model can be integrated into security systems or educational platforms for real-time analysis.

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github-actions bot commented Nov 9, 2024

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

@Ananya-vastare
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@tanishaness please let me know if there are any issues

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@tanishaness please let me know if I need to make any changes because today is the last day thank you

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@tanishaness please respond to this pr thank you

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